{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mikolajboronski/miniconda3/envs/mil/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "from transformers import GPT2LMHeadModel, GPT2Tokenizer\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "transformer.wte.weight torch.Size([50257, 768])\n",
      "transformer.wpe.weight torch.Size([1024, 768])\n",
      "transformer.h.0.ln_1.weight torch.Size([768])\n",
      "transformer.h.0.ln_1.bias torch.Size([768])\n",
      "transformer.h.0.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.0.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.0.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.0.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.0.ln_2.weight torch.Size([768])\n",
      "transformer.h.0.ln_2.bias torch.Size([768])\n",
      "transformer.h.0.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.0.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.0.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.0.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.1.ln_1.weight torch.Size([768])\n",
      "transformer.h.1.ln_1.bias torch.Size([768])\n",
      "transformer.h.1.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.1.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.1.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.1.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.1.ln_2.weight torch.Size([768])\n",
      "transformer.h.1.ln_2.bias torch.Size([768])\n",
      "transformer.h.1.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.1.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.1.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.1.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.2.ln_1.weight torch.Size([768])\n",
      "transformer.h.2.ln_1.bias torch.Size([768])\n",
      "transformer.h.2.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.2.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.2.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.2.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.2.ln_2.weight torch.Size([768])\n",
      "transformer.h.2.ln_2.bias torch.Size([768])\n",
      "transformer.h.2.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.2.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.2.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.2.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.3.ln_1.weight torch.Size([768])\n",
      "transformer.h.3.ln_1.bias torch.Size([768])\n",
      "transformer.h.3.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.3.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.3.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.3.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.3.ln_2.weight torch.Size([768])\n",
      "transformer.h.3.ln_2.bias torch.Size([768])\n",
      "transformer.h.3.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.3.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.3.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.3.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.4.ln_1.weight torch.Size([768])\n",
      "transformer.h.4.ln_1.bias torch.Size([768])\n",
      "transformer.h.4.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.4.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.4.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.4.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.4.ln_2.weight torch.Size([768])\n",
      "transformer.h.4.ln_2.bias torch.Size([768])\n",
      "transformer.h.4.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.4.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.4.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.4.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.5.ln_1.weight torch.Size([768])\n",
      "transformer.h.5.ln_1.bias torch.Size([768])\n",
      "transformer.h.5.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.5.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.5.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.5.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.5.ln_2.weight torch.Size([768])\n",
      "transformer.h.5.ln_2.bias torch.Size([768])\n",
      "transformer.h.5.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.5.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.5.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.5.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.6.ln_1.weight torch.Size([768])\n",
      "transformer.h.6.ln_1.bias torch.Size([768])\n",
      "transformer.h.6.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.6.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.6.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.6.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.6.ln_2.weight torch.Size([768])\n",
      "transformer.h.6.ln_2.bias torch.Size([768])\n",
      "transformer.h.6.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.6.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.6.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.6.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.7.ln_1.weight torch.Size([768])\n",
      "transformer.h.7.ln_1.bias torch.Size([768])\n",
      "transformer.h.7.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.7.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.7.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.7.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.7.ln_2.weight torch.Size([768])\n",
      "transformer.h.7.ln_2.bias torch.Size([768])\n",
      "transformer.h.7.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.7.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.7.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.7.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.8.ln_1.weight torch.Size([768])\n",
      "transformer.h.8.ln_1.bias torch.Size([768])\n",
      "transformer.h.8.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.8.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.8.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.8.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.8.ln_2.weight torch.Size([768])\n",
      "transformer.h.8.ln_2.bias torch.Size([768])\n",
      "transformer.h.8.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.8.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.8.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.8.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.9.ln_1.weight torch.Size([768])\n",
      "transformer.h.9.ln_1.bias torch.Size([768])\n",
      "transformer.h.9.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.9.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.9.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.9.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.9.ln_2.weight torch.Size([768])\n",
      "transformer.h.9.ln_2.bias torch.Size([768])\n",
      "transformer.h.9.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.9.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.9.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.9.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.10.ln_1.weight torch.Size([768])\n",
      "transformer.h.10.ln_1.bias torch.Size([768])\n",
      "transformer.h.10.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.10.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.10.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.10.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.10.ln_2.weight torch.Size([768])\n",
      "transformer.h.10.ln_2.bias torch.Size([768])\n",
      "transformer.h.10.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.10.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.10.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.10.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.h.11.ln_1.weight torch.Size([768])\n",
      "transformer.h.11.ln_1.bias torch.Size([768])\n",
      "transformer.h.11.attn.c_attn.weight torch.Size([768, 2304])\n",
      "transformer.h.11.attn.c_attn.bias torch.Size([2304])\n",
      "transformer.h.11.attn.c_proj.weight torch.Size([768, 768])\n",
      "transformer.h.11.attn.c_proj.bias torch.Size([768])\n",
      "transformer.h.11.ln_2.weight torch.Size([768])\n",
      "transformer.h.11.ln_2.bias torch.Size([768])\n",
      "transformer.h.11.mlp.c_fc.weight torch.Size([768, 3072])\n",
      "transformer.h.11.mlp.c_fc.bias torch.Size([3072])\n",
      "transformer.h.11.mlp.c_proj.weight torch.Size([3072, 768])\n",
      "transformer.h.11.mlp.c_proj.bias torch.Size([768])\n",
      "transformer.ln_f.weight torch.Size([768])\n",
      "transformer.ln_f.bias torch.Size([768])\n",
      "lm_head.weight torch.Size([50257, 768])\n"
     ]
    }
   ],
   "source": [
    "model = GPT2LMHeadModel.from_pretrained('gpt2')\n",
    "state_dict = model.state_dict()\n",
    "\n",
    "for k, v in state_dict.items():\n",
    "    print(k, v.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([ 0.4803, -0.5254, -0.4293,  ...,  0.0126, -0.0499,  0.0032])\n",
      "tensor([ 0.0092, -0.1241, -0.2280,  ...,  0.0404,  0.0494, -0.0038])\n",
      "tensor([-0.0541, -0.0644,  0.0311,  ...,  0.0015, -0.0427,  0.0059])\n",
      "tensor([-0.2251, -0.0644,  0.0223,  ...,  0.0205, -0.0017, -0.0044])\n",
      "tensor([-0.0302,  0.1053,  0.1579,  ..., -0.0185, -0.0097,  0.0927])\n",
      "tensor([-0.0436,  0.0295,  0.0850,  ...,  0.0089, -0.0007,  0.0082])\n",
      "tensor([ 0.0380,  0.1714, -0.1409,  ..., -0.0441,  0.0544,  0.0041])\n",
      "tensor([ 0.3779,  0.0767,  0.0019,  ...,  0.0123, -0.0721,  0.0015])\n",
      "tensor([-0.0167, -0.3909, -0.1419,  ...,  0.0212,  0.0140,  0.0999])\n",
      "tensor([ 0.0571,  0.0355, -0.0991,  ...,  0.0075,  0.0219, -0.0241])\n",
      "tensor([-0.0301,  0.1360, -0.3842,  ..., -0.0599,  0.1059,  0.0276])\n",
      "tensor([-0.2222,  0.0549,  0.0331,  ..., -0.0289, -0.0241,  0.0063])\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, 12):\n",
    "    print(state_dict[f\"transformer.h.{i}.attn.c_attn.bias\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "transformer.h.0.ln_1.bias\n",
      "  tensor(-0.0037)\n",
      "transformer.h.0.attn.c_attn.bias\n",
      "  tensor(0.4803)\n",
      "transformer.h.0.attn.c_proj.bias\n",
      "  tensor(0.1503)\n",
      "transformer.h.0.ln_2.bias\n",
      "  tensor(0.0425)\n",
      "transformer.h.0.mlp.c_fc.bias\n",
      "  tensor(0.0396)\n",
      "transformer.h.0.mlp.c_proj.bias\n",
      "  tensor(0.0450)\n",
      "transformer.h.1.ln_1.bias\n",
      "  tensor(-0.0036)\n",
      "transformer.h.1.attn.c_attn.bias\n",
      "  tensor(0.0092)\n",
      "transformer.h.1.attn.c_proj.bias\n",
      "  tensor(-0.0604)\n",
      "transformer.h.1.ln_2.bias\n",
      "  tensor(0.0202)\n",
      "transformer.h.1.mlp.c_fc.bias\n",
      "  tensor(-0.0624)\n",
      "transformer.h.1.mlp.c_proj.bias\n",
      "  tensor(-0.0231)\n",
      "transformer.h.2.ln_1.bias\n",
      "  tensor(0.0049)\n",
      "transformer.h.2.attn.c_attn.bias\n",
      "  tensor(-0.0541)\n",
      "transformer.h.2.attn.c_proj.bias\n",
      "  tensor(0.0207)\n",
      "transformer.h.2.ln_2.bias\n",
      "  tensor(0.0432)\n",
      "transformer.h.2.mlp.c_fc.bias\n",
      "  tensor(-0.0138)\n",
      "transformer.h.2.mlp.c_proj.bias\n",
      "  tensor(-0.0654)\n",
      "transformer.h.3.ln_1.bias\n",
      "  tensor(0.0236)\n",
      "transformer.h.3.attn.c_attn.bias\n",
      "  tensor(-0.2251)\n",
      "transformer.h.3.attn.c_proj.bias\n",
      "  tensor(-0.0142)\n",
      "transformer.h.3.ln_2.bias\n",
      "  tensor(0.0220)\n",
      "transformer.h.3.mlp.c_fc.bias\n",
      "  tensor(-0.1992)\n",
      "transformer.h.3.mlp.c_proj.bias\n",
      "  tensor(-0.0233)\n",
      "transformer.h.4.ln_1.bias\n",
      "  tensor(0.0224)\n",
      "transformer.h.4.attn.c_attn.bias\n",
      "  tensor(-0.0302)\n",
      "transformer.h.4.attn.c_proj.bias\n",
      "  tensor(-0.1335)\n",
      "transformer.h.4.ln_2.bias\n",
      "  tensor(0.0358)\n",
      "transformer.h.4.mlp.c_fc.bias\n",
      "  tensor(-0.0643)\n",
      "transformer.h.4.mlp.c_proj.bias\n",
      "  tensor(-0.0590)\n",
      "transformer.h.5.ln_1.bias\n",
      "  tensor(0.0201)\n",
      "transformer.h.5.attn.c_attn.bias\n",
      "  tensor(-0.0436)\n",
      "transformer.h.5.attn.c_proj.bias\n",
      "  tensor(-0.0348)\n",
      "transformer.h.5.ln_2.bias\n",
      "  tensor(0.0420)\n",
      "transformer.h.5.mlp.c_fc.bias\n",
      "  tensor(-0.0782)\n",
      "transformer.h.5.mlp.c_proj.bias\n",
      "  tensor(-0.0265)\n",
      "transformer.h.6.ln_1.bias\n",
      "  tensor(0.0233)\n",
      "transformer.h.6.attn.c_attn.bias\n",
      "  tensor(0.0380)\n",
      "transformer.h.6.attn.c_proj.bias\n",
      "  tensor(-0.0478)\n",
      "transformer.h.6.ln_2.bias\n",
      "  tensor(0.0450)\n",
      "transformer.h.6.mlp.c_fc.bias\n",
      "  tensor(-0.0303)\n",
      "transformer.h.6.mlp.c_proj.bias\n",
      "  tensor(-0.0328)\n",
      "transformer.h.7.ln_1.bias\n",
      "  tensor(0.0303)\n",
      "transformer.h.7.attn.c_attn.bias\n",
      "  tensor(0.3779)\n",
      "transformer.h.7.attn.c_proj.bias\n",
      "  tensor(-0.0378)\n",
      "transformer.h.7.ln_2.bias\n",
      "  tensor(0.0480)\n",
      "transformer.h.7.mlp.c_fc.bias\n",
      "  tensor(-0.0441)\n",
      "transformer.h.7.mlp.c_proj.bias\n",
      "  tensor(0.0030)\n",
      "transformer.h.8.ln_1.bias\n",
      "  tensor(0.0266)\n",
      "transformer.h.8.attn.c_attn.bias\n",
      "  tensor(-0.0167)\n",
      "transformer.h.8.attn.c_proj.bias\n",
      "  tensor(0.0141)\n",
      "transformer.h.8.ln_2.bias\n",
      "  tensor(0.0265)\n",
      "transformer.h.8.mlp.c_fc.bias\n",
      "  tensor(-0.1121)\n",
      "transformer.h.8.mlp.c_proj.bias\n",
      "  tensor(-0.0588)\n",
      "transformer.h.9.ln_1.bias\n",
      "  tensor(0.0305)\n",
      "transformer.h.9.attn.c_attn.bias\n",
      "  tensor(0.0571)\n",
      "transformer.h.9.attn.c_proj.bias\n",
      "  tensor(-0.0726)\n",
      "transformer.h.9.ln_2.bias\n",
      "  tensor(0.0464)\n",
      "transformer.h.9.mlp.c_fc.bias\n",
      "  tensor(-0.1567)\n",
      "transformer.h.9.mlp.c_proj.bias\n",
      "  tensor(-0.0466)\n",
      "transformer.h.10.ln_1.bias\n",
      "  tensor(0.0305)\n",
      "transformer.h.10.attn.c_attn.bias\n",
      "  tensor(-0.0301)\n",
      "transformer.h.10.attn.c_proj.bias\n",
      "  tensor(-0.0124)\n",
      "transformer.h.10.ln_2.bias\n",
      "  tensor(-0.0104)\n",
      "transformer.h.10.mlp.c_fc.bias\n",
      "  tensor(-0.0678)\n",
      "transformer.h.10.mlp.c_proj.bias\n",
      "  tensor(-0.0381)\n",
      "transformer.h.11.ln_1.bias\n",
      "  tensor(0.0510)\n",
      "transformer.h.11.attn.c_attn.bias\n",
      "  tensor(-0.2222)\n",
      "transformer.h.11.attn.c_proj.bias\n",
      "  tensor(0.1185)\n",
      "transformer.h.11.ln_2.bias\n",
      "  tensor(-0.0020)\n",
      "transformer.h.11.mlp.c_fc.bias\n",
      "  tensor(-0.0382)\n",
      "transformer.h.11.mlp.c_proj.bias\n",
      "  tensor(0.1057)\n",
      "transformer.ln_f.bias\n",
      "  tensor(0.0011)\n"
     ]
    }
   ],
   "source": [
    "for k in state_dict.keys():\n",
    "    if \"bias\" in k: \n",
    "        print(k)\n",
    "        print(\" \", state_dict[k][0])\n",
    "# for k in state_dict.keys():\n",
    "#     # if \"bias\" in k: \n",
    "#     if len(state_dict[k][0].shape) == 2:\n",
    "#         if state_dict[k][0] == -0.0198:\n",
    "#             print(k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.1101, -0.0393,  0.0331,  0.1338, -0.0485, -0.0789, -0.2398, -0.0895,\n",
       "         0.0253, -0.1074, -0.1811, -0.0672,  0.0739, -0.0161,  0.0117,  0.1245,\n",
       "        -0.0020, -0.0815,  0.0338,  0.2365])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_dict[\"transformer.wte.weight\"].view(-1)[:20] # flattened token embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.0188, -0.1974,  0.0040,  0.0113,  0.0638, -0.1050,  0.0369, -0.1680,\n",
       "        -0.0491, -0.0565, -0.0025,  0.0135, -0.0042,  0.0151,  0.0166, -0.1381,\n",
       "        -0.0063, -0.0461,  0.0267, -0.2042])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_dict[\"transformer.wpe.weight\"].view(-1)[:20] # flattened position embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1024, 768])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x33b645f30>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(state_dict[\"transformer.wpe.weight\"].shape) # (1024, 768), 1024 is the context length for GPT-2\n",
    "plt.figure(figsize=(10, 10))\n",
    "plt.imshow(state_dict[\"transformer.wpe.weight\"]) \n",
    "# there is a structure somewhat visible, cause every row here is different position encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x33b84b3d0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(state_dict[\"transformer.wpe.weight\"][:, 20], alpha=0.5, label=\"20th position\")\n",
    "plt.plot(state_dict[\"transformer.wpe.weight\"][:, 50], alpha=0.5, label=\"50th position\")\n",
    "plt.plot(state_dict[\"transformer.wpe.weight\"][:, 700], alpha=0.5, label=\"700th position\")\n",
    "plt.legend()\n",
    "\n",
    "# each of the lines is responsible for scaling one of 768 dimensions of the token embeddings\n",
    "# for example: \n",
    "#   blue line tends to make tokens after 900th position smaller\n",
    "#   orange line tends to make tokens after 900th position larger\n",
    "\n",
    "# according to Karpathy: the way these embedding lines are noisy, tells that the model\n",
    "# could be train a little more, and is undertrained right now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x33b970ac0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(state_dict[\"transformer.h.1.attn.c_attn.weight\"][:100, :100])\n",
    "# yeah there is something, possibly, maybe\n",
    "# but thats when i get to mechanistic interptretability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "tokenizer_config.json: 100%|██████████| 26.0/26.0 [00:00<00:00, 158kB/s]\n",
      "vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 2.16MB/s]\n",
      "merges.txt: 100%|██████████| 456k/456k [00:00<00:00, 1.36MB/s]\n",
      "tokenizer.json: 100%|██████████| 1.36M/1.36M [00:00<00:00, 2.47MB/s]\n",
      "Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=True` to explicitly truncate examples to max length. Defaulting to 'longest_first' truncation strategy. If you encode pairs of sequences (GLUE-style) with the tokenizer you can select this strategy more precisely by providing a specific strategy to `truncation`.\n",
      "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[{'generated_text': \"Hello, I'm a language model, I'm writing a new language for you. But first,\"},\n",
       " {'generated_text': \"Hello, I'm a language model, and I'm trying to be as expressive as possible. In\"},\n",
       " {'generated_text': \"Hello, I'm a language model, so I don't get much of a license anymore, but\"},\n",
       " {'generated_text': \"Hello, I'm a language model, a functional model... It's not me, it's me\"},\n",
       " {'generated_text': \"Hello, I'm a language model, not an object model.\\n\\nIn a nutshell, I\"}]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from transformers import set_seed, pipeline\n",
    "generator = pipeline('text-generation', model=model, tokenizer=GPT2Tokenizer.from_pretrained('gpt2'))\n",
    "set_seed(42)\n",
    "generator(\"Hello, I'm a language model,\", max_length=20, num_return_sequences=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First Citizen:\n",
      "Before we proceed any further, hear me speak.\n",
      "\n",
      "All:\n",
      "Speak, speak.\n",
      "\n",
      "First Citizen:\n",
      "You\n",
      "[5962, 22307, 25, 198, 8421, 356, 5120, 597, 2252, 11, 3285, 502, 2740, 13, 198, 198, 3237, 25, 198, 5248, 461, 11, 2740, 13]\n"
     ]
    }
   ],
   "source": [
    "with open(\"input.txt\", \"r\") as f:\n",
    "    text = f.read()\n",
    "data = text[:1000]\n",
    "print(data[:100])\n",
    "\n",
    "import tiktoken\n",
    "enc = tiktoken.get_encoding(\"gpt2\")\n",
    "tokens = enc.encode(data)\n",
    "print(tokens[:24])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   40000  202651 1115394 input.txt\n",
      "tensor([[ 5962, 22307,    25,   198],\n",
      "        [ 8421,   356,  5120,   597],\n",
      "        [ 2252,    11,  3285,   502],\n",
      "        [ 2740,    13,   198,   198],\n",
      "        [ 3237,    25,   198,  5248],\n",
      "        [  461,    11,  2740,    13]])\n",
      "tensor([[ 5962, 22307,    25,   198],\n",
      "        [ 8421,   356,  5120,   597],\n",
      "        [ 2252,    11,  3285,   502],\n",
      "        [ 2740,    13,   198,   198],\n",
      "        [ 3237,    25,   198,  5248],\n",
      "        [  461,    11,  2740,    13]])\n",
      "tensor([[ 5962, 22307,    25,   198],\n",
      "        [ 8421,   356,  5120,   597],\n",
      "        [ 2252,    11,  3285,   502],\n",
      "        [ 2740,    13,   198,   198],\n",
      "        [ 3237,    25,   198,  5248],\n",
      "        [  461,    11,  2740,    13]])\n",
      "tensor([[22307,    25,   198,  8421],\n",
      "        [  356,  5120,   597,  2252],\n",
      "        [   11,  3285,   502,  2740],\n",
      "        [   13,   198,   198,  3237],\n",
      "        [   25,   198,  5248,   461],\n",
      "        [   11,  2740,    13,   198]])\n"
     ]
    }
   ],
   "source": [
    "# now this big ass text\n",
    "!wc input.txt\n",
    "# 40000 lines\n",
    "# 202651 words\n",
    "# 1115394 bytes (~letters)\n",
    "# needs to be chunked into parts that we can feed the transformer with\n",
    "\n",
    "# Andrej says this is a good way to do it, I listen\n",
    "import torch\n",
    "buf = torch.tensor(tokens[:24])\n",
    "x   = buf.view(6, 4)\n",
    "x2  = buf.reshape(6, 4)\n",
    "print(x)\n",
    "print(x2)\n",
    "# apparently reshape is better since it can handle non-contigous tensors\n",
    "# but with view you can be sure that it will use the same memory area as the viewed object\n",
    "# reshape may or may not return a copy\n",
    "\n",
    "# also a simple way to do both training data and labels, is just taking t and t+1\n",
    "buf = torch.tensor(tokens[:24 + 1])\n",
    "x   = buf[:-1].view(6, 4)\n",
    "y   = buf[1:].view(6, 4)\n",
    "print(x)\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How variance grows in residual streams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x335137280>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import numpy as np\n",
    "\n",
    "x = torch.randn(768)\n",
    "temporary_x_std = [x.std()]\n",
    "temporary_x_std_normed = [x.std()]\n",
    "for i in range(100):\n",
    "    x += torch.randn(768)\n",
    "    temporary_x_std.append(x.std())\n",
    "    temporary_x_std_normed.append(x.std()/math.sqrt(i+2))\n",
    "\n",
    "plt.figure(figsize=(10, 3))\n",
    "plt.title(\"Scaled vs non-scaled std of stacked layers in residual streams\")\n",
    "plt.plot(temporary_x_std, marker=\"o\", alpha=0.5, label=\"non-scaled\")\n",
    "plt.plot(temporary_x_std_normed, marker=\"o\", alpha=0.5, label=\"scaled\")\n",
    "plt.yticks(np.arange(0, 10, 1))\n",
    "plt.grid()\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the above is not really right, we want the **accumulated** std to be equal to 1 so that after a forward pass the total growth is controlled\n",
    "\n",
    "im still unsure about this, but it has a notion of sense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x3343be260>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import numpy as np\n",
    "\n",
    "x = torch.randn(768)\n",
    "temporary_x_std = [x.std()]\n",
    "temporary_x_std_normed = [x.std()/100]\n",
    "for i in range(100):\n",
    "    x += torch.randn(768)\n",
    "    temporary_x_std.append(x.std())\n",
    "    temporary_x_std_normed.append(x.std()/math.sqrt(100))\n",
    "\n",
    "plt.figure(figsize=(10, 3))\n",
    "plt.title(\"Scaled vs non-scaled std of stacked layers in residual streams\")\n",
    "plt.plot(temporary_x_std, marker=\"o\", alpha=0.5, label=\"non-scaled\")\n",
    "plt.plot(temporary_x_std_normed, marker=\"o\", alpha=0.5, label=\"scaled\")\n",
    "plt.yticks(np.arange(0, 10, 1))\n",
    "plt.ylabel(\"std\")\n",
    "plt.xlabel(\"n_layer\")\n",
    "plt.grid()\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([8.3957e-04, 5.4092e-04, 3.0088e-04,  ..., 4.1868e-05, 2.6622e-04,\n",
      "        2.0828e-05])\n",
      "tensor([8.3957e-04, 5.4092e-04, 3.0088e-04,  ..., 4.1868e-05, 2.6622e-04,\n",
      "        2.0828e-05])\n",
      "tensor([8.3957e-04, 5.4092e-04, 3.0088e-04,  ..., 4.1868e-05, 2.6622e-04,\n",
      "        2.0828e-05])\n",
      "tensor([8.3957e-04, 5.4092e-04, 3.0088e-04,  ..., 4.1868e-05, 2.6622e-04,\n",
      "        2.0828e-05])\n",
      "Ground truth and custom softmax are equal: True\n",
      "Ground truth and safe softmax are equal: True\n",
      "Ground truth and online safe softmax are equal: True\n",
      "Ground truth and online safe softmax list are equal: True\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "from torch.nn import functional as F\n",
    "from gpt2 import softmax, safe_softmax, online_safe_softmax, online_safe_softmax_list\n",
    "\n",
    "torch.manual_seed(42)\n",
    "\n",
    "# if you dont cast long to float F.softmax throws \n",
    "# RuntimeError: \"softmax_lastdim_kernel_impl\" not implemented for 'Long' lol\n",
    "x = torch.tensor([1000, 999, 998], dtype=torch.float)\n",
    "x = torch.randn(5000)\n",
    "s = softmax()\n",
    "ss = safe_softmax()\n",
    "oss = online_safe_softmax()\n",
    "ossl = online_safe_softmax_list()\n",
    "\n",
    "ground_truth = F.softmax(x, dim=0)\n",
    "rs = s(x, np)\n",
    "rss = ss(x, np)\n",
    "ross = oss(x, np)\n",
    "rossl = ossl(x, np)\n",
    "\n",
    "print(ground_truth)\n",
    "print(rs)\n",
    "print(rss)\n",
    "print(ross)\n",
    "\n",
    "print(f\"Ground truth and custom softmax are equal: {torch.allclose(ground_truth, rs)}\")\n",
    "print(f\"Ground truth and safe softmax are equal: {torch.allclose(ground_truth, rss)}\")\n",
    "print(f\"Ground truth and online safe softmax are equal: {torch.allclose(ground_truth, ross)}\")\n",
    "print(f\"Ground truth and online safe softmax list are equal: {torch.allclose(ground_truth, rossl)}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "46.2 ms ± 973 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
      "63.7 ms ± 608 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
      "91.7 ms ± 684 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
      "91.8 ms ± 1.06 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
      "9 μs ± 21.9 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit s(x, np)\n",
    "%timeit ss(x, np)\n",
    "%timeit oss(x, np)\n",
    "%timeit ossl(x, np)\n",
    "%timeit F.softmax(x, dim=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import timeit\n",
    "results = {\n",
    "    s: {\"mean\": [], \"std\": []},\n",
    "    ss: {\"mean\": [], \"std\": []},\n",
    "    oss: {\"mean\": [], \"std\": []},\n",
    "    ossl: {\"mean\": [], \"std\": []},\n",
    "    F.softmax: {\"mean\": [], \"std\": []}\n",
    "}\n",
    "for n in [10, 100, 1000, 10000]:\n",
    "    x = torch.randn(n)\n",
    "    results[s][\"mean\"].append(timeit.timeit(lambda: s(x, np), number=10))\n",
    "    results[ss][\"mean\"].append(timeit.timeit(lambda: ss(x, np), number=10))\n",
    "    results[oss][\"mean\"].append(timeit.timeit(lambda: oss(x, np), number=10))\n",
    "    results[ossl][\"mean\"].append(timeit.timeit(lambda: ossl(x, np), number=10))\n",
    "    results[F.softmax][\"mean\"].append(timeit.timeit(lambda: F.softmax(x, dim=0), number=10))\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{softmax(): {'mean': [0.0033158750011352822,\n",
       "   0.013601957994978875,\n",
       "   0.09257387499383185,\n",
       "   0.9358634579984937,\n",
       "   9.13603791600326],\n",
       "  'std': []},\n",
       " safe_softmax(): {'mean': [0.00266116599959787,\n",
       "   0.01675616600550711,\n",
       "   0.12795383301272523,\n",
       "   1.2847402500046883,\n",
       "   12.610043916007271],\n",
       "  'std': []},\n",
       " online_safe_softmax(): {'mean': [0.0033562919998075813,\n",
       "   0.022060917006456293,\n",
       "   0.18585229200834874,\n",
       "   1.8503058750065975,\n",
       "   18.32050362500013],\n",
       "  'std': []},\n",
       " online_safe_softmax_list(): {'mean': [0.0032640830031596124,\n",
       "   0.020861208002315834,\n",
       "   0.18536625000706408,\n",
       "   1.82898020799621,\n",
       "   18.46620900000562],\n",
       "  'std': []},\n",
       " <function torch.nn.functional.softmax(input: torch.Tensor, dim: Optional[int] = None, _stacklevel: int = 3, dtype: Optional[int] = None) -> torch.Tensor>: {'mean': [0.00040704199636820704,\n",
       "   2.2332998923957348e-05,\n",
       "   3.470800584182143e-05,\n",
       "   0.000185875003808178,\n",
       "   0.0016898750036489218],\n",
       "  'std': []}}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fineweb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datasets\n",
    "from datasets import load_dataset\n",
    "\n",
    "dataset = load_dataset(\"HuggingFaceFW/fineweb-edu\", \"sample-10BT\", split=\"train\", streaming=True)\n",
    "\n",
    "# next(iter(dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'text': 'The Independent Jane\\nFor all the love, romance and scandal in Jane Austen’s books, what they are really about is freedom and independence. Independence of thought and the freedom to choose.\\nElizabeth’s refusal of Mr. Collins offer of marriage showed an independence seldom seen in heroines of the day. Her refusal of Mr. Darcy while triggered by anger showed a level of independence that left him shocked and stunned.\\nThe freedom she exhibited in finally accepting him in direct defiance of Lady Catherine and knowing her father would disapprove was unusual even for Austen. In her last book Anne Elliot is persuaded to refuse Captain Wentworth at Lady Russel’s insistence.\\nAlthough Jane played by the rules of the day, all of her writing is infused with how she wanted life to be. She ‘screams’ her outrage at the limitations for women in Emma.\\nWhen accosted by Mrs. Elton, Jane Fairfax says,\\n“Excuse me, ma’am, but this is by no means my intention; I make no inquiry myself, and should be sorry to have any made by my friends. When I am quite determined as to the time, I am not at all afraid of being long unemployed. There are places in town, offices, where inquiry would soon produce something — offices for the sale, not quite of human flesh, but of human intellect.”\\n“Oh! my dear, human flesh! You quite shock me; if you mean a fling at the slave-trade, I assure you Mr. Suckling was always rather a friend to the abolition.”\\n“I did not mean, I was not thinking of the slave-trade,” replied Jane; “governess-trade, I assure you, was all that I had in view; widely different certainly, as to the guilt of those who carry it on; but as to the greater misery of the victims, I do not know where it lies.”\\nThat same sentiment is emphasized in Emma’s shock when Mrs. Weston tells her of Frank Churchill’s secret engagement to Jane.\\n“Good God!” cried Emma, “Jane actually on the point of going as governess! What could he mean by such horrible indelicacy? To suffer her to engage herself — to suffer her even to think of such a measure!”\\nI find it interesting that at the moment of Austen’s birth or there about, John Adams left his farm in Massachusetts for the Continental Congress in Philadelphia. Doesn’t sound particularly interesting, I know but consider this.\\nJohn Adams left his home in mid-December 1775 to attend an unprecedented meeting of colonial representatives to consider severing ties with their mother country and her monarch; a decision that culminated in a document unlike any ever written. In the mother country, one day in that same cold December a baby girl was born at Steventon Rectory. Her cry was heard by only the people in the house but the years to come would see her pen create works unlike any the world had ever seen.\\nComparing Austen’s words with Thomas Jefferson’s may seem a trivialization but I believe that Austen’s impact on the world is no less important than Jefferson’s. The effect of Jane’s writing maybe more subtle than that of the Virginian but it is no less influential.\\nJefferson’s words instigated and promoted a revolution, a war of independence. Jane’s words had no such excessive consequence. Still in her own quiet, genteel yet powerful way she declared and promoted the same principles of freedom and self-regulated independence as our American forefathers. In all her novels Jane advocates independence of person and thought, the rights of all and acceptance of responsibility for those rights.\\nJane may not have incited military action as Jefferson did but even as an avowed royalist, I doubt not that Jane Austen firmly believed in his declaration of the right to life, liberty and the pursuit of happiness.',\n",
       " 'id': '<urn:uuid:0d8a309d-25c5-405d-a08a-c11239f0d717>',\n",
       " 'dump': 'CC-MAIN-2013-20',\n",
       " 'url': 'http://austenauthors.net/the-independent-jane',\n",
       " 'file_path': 's3://commoncrawl/crawl-data/CC-MAIN-2013-20/segments/1368696381249/warc/CC-MAIN-20130516092621-00000-ip-10-60-113-184.ec2.internal.warc.gz',\n",
       " 'language': 'en',\n",
       " 'language_score': 0.9743200540542603,\n",
       " 'token_count': 845,\n",
       " 'score': 2.75,\n",
       " 'int_score': 3}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(iter(dataset))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Local Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'gpt2'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[3], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mgpt2\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m GPT\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'gpt2'"
     ]
    }
   ],
   "source": [
    "from gpt2 import GPT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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